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Emmett Fear

Emmett Fear

Emmett runs Growth at Runpod. He lives in Utah with his wife and dog, and loves to spend time hiking and paddleboarding. He has worked in many different facets of tech, from marketing, operations, product, and most recently, growth.

Deploying Open-Sora for AI Video Generation on RunPod Using Docker Containers

Deploy Open-Sora for AI-powered video generation on Runpod’s high-performance GPUs—create text-to-video clips in minutes using Dockerized workflows, scalable cloud pods, and serverless endpoints with pay-per-second pricing.
Guides

Fine-Tuning Llama 3.1 on RunPod: A Step-by-Step Guide for Efficient Model Customization

Fine-tune Meta’s Llama 3.1 using LoRA on Runpod’s high-performance GPUs—train custom LLMs cost-effectively with A100 or H100 instances, Docker containers, and per-second billing for scalable, infrastructure-free AI development.
Guides

Quantum-Inspired AI Algorithms: Accelerating Machine Learning with RunPod's GPU Infrastructure

Accelerate quantum-inspired machine learning with Runpod—simulate quantum algorithms on powerful GPUs like H100 and A100, reduce costs with per-second billing, and deploy scalable, cutting-edge AI workflows without quantum hardware.
Guides

Multimodal AI Deployment Guide: Running Vision-Language Models on RunPod GPUs

Instantly launch GPU-accelerated environments with RunPod’s Deploy Console—spin up containers, models, or templates on demand with scalable performance and transparent per-second pricing.
Guides

Unlocking High‑Performance Machine Learning with JAX on Runpod

Accelerate machine learning with JAX on Runpod—leverage JIT compilation, auto-vectorization, and scalable GPU clusters to train cutting-edge models faster and more affordably than ever before.
Guides

Maximizing Efficiency: Fine‑Tuning Large Language Models with LoRA and QLoRA on Runpod

Fine-tune large language models affordably using LoRA and QLoRA on Runpod—cut VRAM requirements by up to 4×, reduce costs with per-second billing, and deploy custom LLMs in minutes using scalable GPU infrastructure.
Guides

Scaling Up Efficiently: Distributed Training with DeepSpeed and ZeRO on Runpod

Train billion-parameter models efficiently with DeepSpeed and ZeRO on Runpod’s scalable GPU infrastructure—reduce memory usage, cut costs, and accelerate training using per-second billing and Instant Clusters.
Guides

How do I build a scalable, low‑latency speech recognition pipeline on Runpod using Whisper and GPUs?

Deploy real-time speech recognition with Whisper and faster-whisper on Runpod’s GPU cloud—optimize latency, cut costs, and transcribe multilingual audio at scale using serverless or containerized ASR pipelines.
Guides

Unleashing Graph Neural Networks on Runpod’s GPUs: Scalable, High‑Speed GNN Training

Accelerate graph neural network training with GPU-powered infrastructure on Runpod—scale across clusters, cut costs with per-second billing, and deploy distributed GNN models for massive graphs in minutes.
Guides

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The most cost-effective platform for building, training, and scaling machine learning models—ready when you are.

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